# import akshare as ak
#
# stock_sse_summary = ak.stock_sse_summary()
# print(stock_sse_summary)
# print(type(stock_sse_summary))
import matplotlib
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
import mpld3
from mpld3 import plugins
# matplotlib.use('TkAgg')
# plt.title('Training history')
# plt.ylabel('Accuracy')
# plt.xlabel('Epoch')
# plt.legend()
# plt.ylim([0, 1])
# plt.show()

#
# np.random.seed(9615)
#
# # generate df
# N = 100
# df = pd.DataFrame((.1 * (np.random.random((N, 5)) - .5)).cumsum(0),
#                   columns=['a', 'b', 'c', 'd', 'e'], )
#
# # plot line + confidence interval
# fig, ax = plt.subplots()
# ax.grid(True, alpha=0.3)
#
# for key, val in df.items():
#     l, = ax.plot(val.index, val.values, label=key)
#     ax.fill_between(val.index,
#                     val.values * .5, val.values * 1.5,
#                     color=l.get_color(), alpha=.4)
#
# # define interactive legend
#
# handles, labels = ax.get_legend_handles_labels()  # return lines and labels
# interactive_legend = plugins.InteractiveLegendPlugin(zip(handles,
#                                                          ax.collections),
#                                                      labels,
#                                                      alpha_unsel=0.5,
#                                                      alpha_over=1.5,
#                                                      start_visible=True)
# plugins.connect(fig, interactive_legend)
#
# ax.set_xlabel('x')
# ax.set_ylabel('y')
# ax.set_title('Interactive legend', size=20)
#
# mpld3.show()

import time
t=time.time()-604800#计算七天前的时间戳
today=time.localtime()#获取今天的日期
ago=time.localtime(t)#获取七天前的日期

today_m=int(today.tm_mon)
today_d=int(today.tm_mday)
ago_m=int(ago.tm_mon)
ago_d=int(ago.tm_mday)
